Academics

Graduate Program

Academics

Graduate Program

Graduate Program

Convex Optimization Techniques

Subject No.
Research
Credit
Classification
Prerequisite
EE523
Computer, Communication, Signal
3
72

The main goal of this course is to present advanced topics of convex optimization which are essential for researches in communications and networks, estimation and signal processing, data analysis and modeling, statistics and finance, electronic circuit design, automatic control, and industrial engineering and to deal with their application areas. We study the primal-dual interior point method, semi-definite programs, and second-order cone programs.

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Signal, Communication
EE432

This course studies the representation, analysis, and design of discrete-time signals and systems. Topics include a review of the z-transform and the discrete Fourier transform, the fast Fourier transform, digital filter structures, digital filter design techniques, analog-to-digital, and digital-to-analog data conversion, rate conversion, sampling and aliasing issues. (Prerequisite: EE202)

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Communication, Signal
EE202

This course is an introduction to continuous-time and discrete-time signals and systems. The course covers Fourier series, Fourier transform, Laplace transform, and z-transform. Various types of systems with emphasis on linear time invariant system is studied.

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Wave
EE204

This course covers introductory electromagnetic fields and waves. Static electric fields and static magnetic fields are discussed. Time-varying fields and Maxwell’s equations are introduced. Waves and transmission lines are studied.

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This course covers data structures, algorithms, JAVA for electron electronics engineering. We study object-oriented programming techniques and use programming language C, JAVA.

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Signal, Wave, Communication, Computer, Circuit, Device
EE305

Experiments related to electronics are performed. Focus is made for both hands-on experience and design practice. (Prerequisite: EE201, EE304)

 

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